Vibe coding is a way of building software where you describe what you want in plain language, let an AI tool such as Claude write the code, and steer by running the result and asking for changes, often without reading every line. It is excellent for prototypes, internal helpers and learning. It is risky for anything that handles customer data, money or security, unless a person who understands the code reviews and tests it before it goes live.
What vibe coding actually means
The term describes a working style rather than a product. Instead of writing code line by line, you give an instruction such as "build a simple page that lets staff upload a spreadsheet and shows totals by branch". The AI produces a working version. You try it, say what is wrong, and the AI revises. The loop continues until it behaves the way you want.
The "vibe" part is that the person often accepts the code on trust, judging it by whether the app seems to work. That is what separates it from ordinary AI-assisted development, where an engineer reads, understands and tests what the AI suggests. Tools such as Claude Code can be used in either style; the difference is in how much human review sits around them.
Where vibe coding helps a business
- Prototypes. Turning an idea into something clickable in hours lets a team test whether it is worth building properly.
- Internal helpers. A small tool that renames files, reformats a report or tidies a data export can save real time for one team.
- Learning. Non-programmers learn what is possible and how software behaves by building small things.
- Communicating requirements. A rough working demo is often a clearer brief for developers than a long document.
Where vibe coding becomes risky
Code that looks like it works can still be wrong, insecure or impossible to maintain. The risk grows with the stakes.
- Hidden bugs. The app may handle the example you tried and fail on the next case. AI can produce confident but incorrect output, the same issue described in what an AI hallucination is.
- Security gaps. Login, permissions, file uploads and stored credentials are easy to get subtly wrong, and a non-programmer may not know what to look for.
- Personal and confidential data. Putting real customer records into a tool, or into a prototype, raises the same questions covered in whether you can put customer data into Claude.
- No owner. If the person who built it leaves, nobody may understand how it works. This is a quieter cousin of shadow AI: tools that run the business without anyone formally responsible for them.
- Maintenance. Software needs updates and fixes. A tool nobody can read is hard to change safely.
A simple rule: match the review to the stakes
| What you are building | Suggested approach |
|---|---|
| Personal helper using no sensitive data | Vibe coding is fine; test it on a few cases. |
| Team tool using internal, non-sensitive data | Have someone technical skim it; name an owner; keep a copy of the instructions used. |
| Anything touching customer data, payments or logins | Treat it as normal software: an engineer reviews it, tests it, and it follows your security process. |
This is the same principle as human-in-the-loop: the more costly a mistake, the more a knowledgeable person should check before it takes effect.
How to vibe code more safely
- Start with fake or sample data. Never paste real customer or staff records into a prototype.
- Ask the AI to explain the code. Request a plain-language walkthrough and a list of assumptions and known limitations.
- Write tests, or have the AI write them. Include unusual cases, empty inputs and wrong inputs, not only the happy path.
- Ask for a security review. An AI review is a useful first pass, not a substitute for a qualified person on important systems.
- Keep everything in version control. Save the code and the prompts so changes can be traced and undone.
- Name an owner and a purpose. Record who maintains the tool, what it is for and when it should be retired.
What this means for managers
Vibe coding lowers the barrier to building software, so people outside IT will build things, with or without permission. A sensible response is to set expectations rather than ban it: say which kinds of tools staff may build, what data they may use, and when IT or security must be involved. Your company AI policy is the natural place for this; see what a company AI usage policy should include. If regulated or personal data is involved, this is general information, not legal advice; confirm with your legal or compliance team.
Learning to use AI for building, responsibly
Good results come from clear instructions, careful checking and knowing when to hand over to a specialist. These habits are covered in the two-day Claude Certified Architect workshop for people designing solutions with Claude, and the broader skills of working safely with AI are part of our AI training in Malaysia. The workshops are run by Agmo Studio, a Select Partner of the Anthropic Claude Partner Network. Certifications are issued by Anthropic; Agmo runs the exam-preparation workshops.